Most store owners have the same problem: they can’t see their own store the way a stranger does. They know where every button is, they’ve dismissed every pop-up and they read their product copy with full context. (I wrote more about that in friction blindness.) StorePeek exists to be that stranger, on demand.
The flow is short: paste a store URL, wait a minute or two, and get back a list of problems ranked by how much they’re likely to cost you. Behind that are four steps.
1. Load the store like a real shopper
The first decision was to look at stores in a real browser rather than fetching their HTML. A modern store is barely there in its source code. Themes render with JavaScript, apps inject review widgets and chat bubbles, and pop-ups fire after a delay. What decides whether someone buys is what ends up on the screen, not what’s in the markup.
So StorePeek opens each store in Chrome twice: once at desktop size and once as a phone. It captures the first impression exactly as a visitor gets it, pop-ups and all, because that first screen is part of the experience. Then it closes cookie banners and newsletter pop-ups to see the page underneath.
It only ever visits public pages, the same ones any shopper can see. There’s no login, no app to install and no tracking script, and the screenshots are deleted once the analysis is done. That keeps the barrier to trying it close to zero, which matters when the whole point is a quick second opinion.
2. Let the AI look, not read
The screenshots go to Google’s Gemini model, which reviews them against a conversion checklist. Working from images instead of code is deliberate: many of the problems that cost sales are visual. Is the add-to-cart button above the fold on a phone? Does the headline say what the store sells? Do the reviews sit next to the price, or three scrolls down? You can’t answer those from HTML alone.
The checklist matters as much as the model. Ask an AI an open question like “how can this store improve?” and you get generic advice that would fit any website. Asking it to check specific areas keeps the output concrete:
- First impressions: is it clear within seconds what’s on sale and why to buy here?
- Trust and credibility: reviews, guarantees, policies and payment badges.
- Path to purchase: buttons that get lost, confusing navigation, dead ends between landing and add-to-cart.
- Mobile readability, pricing clarity, and whether shipping and returns information is easy to find.
3. Measure speed with a tool everyone trusts
For performance, StorePeek runs Google PageSpeed and reports First Contentful Paint, Speed Index and Cumulative Layout Shift. I could have built a custom speed score, but there’s no reason to. PageSpeed is what store owners, developers and agencies already use, so a number from StorePeek means the same thing as the number their developer sees. A shared vocabulary makes the fix easier to hand over.
4. Rank everything
A list of thirty problems with no order is almost as useless as no list at all. You don’t know where to start, so you don’t. Every issue StorePeek finds therefore gets a severity (High, Medium or Low), an explanation of why it costs sales, and a specific fix. “Improve your trust signals” isn’t a fix; “show your star rating and review count next to the price” is.
The findings also roll up into a friction score from 0 to 10, based on how many issues were found and how severe they are. It isn’t meant as a grade. It’s a way to see whether a change moved things in the right direction the next time you run a check.
What the AI is good at, and what it isn’t
The model is good at spotting the common patterns that hurt conversion: a buried call to action, missing reassurance near the buy button, a hero image that says nothing about the product. Those are the problems that show up again and again, and they’re exactly the ones owners stop noticing.
It’s not good at knowing your customers. It doesn’t know that your audience expects a long story before buying, or that a design choice that looks odd is deliberate. That’s why the report is framed as an expert second opinion, not a verdict. The same goes for the “sales lost” estimate on paid plans: it’s a rough guide based on the issues found, not a measurement of your actual revenue.
The goal isn’t to replace your judgement. It’s to give you a fresh pair of eyes every time you need one.
See it for yourself
The quickest way to understand StorePeek is to look at an example report, or to run a free audit on your own store. If you’d like the product story in one place, there’s also a StorePeek case study on this site.